Self-Organizing Migrating Algorithm  Methodology and Implementation /  [electronic resource] : 
edited by Donald Davendra, Ivan Zelinka. 
 - 1st ed. 2016. 
 - XVIII, 289 p. 128 illus., 87 illus. in color.  online resource. 
 - Studies in Computational Intelligence,  626  1860-9503 ; .
 - Studies in Computational Intelligence,  626 .
<br/><br/> This book brings together the current state of-the-art research in Self Organizing Migrating Algorithm (SOMA) as a novel population-based evolutionary algorithm, modeled on the predator-prey relationship, by its leading practitioners. As the first ever book on SOMA, this book is geared towards graduate students, academics and researchers, who are looking for a good optimization algorithm for their applications. This book presents the methodology of SOMA, covering both the real and discrete domains, and its various implementations in different research areas. The easy-to-follow and implement methodology used in the book will make it easier for a reader to implement, modify and utilize SOMA. . 
<br/><br/><label>ISBN: </label>9783319281612 
<br/><br/><label>Standard No.: </label>10.1007/978-3-319-28161-2  doi 
<br/><br/><label>Subjects--Topical Terms: </label><br/>Computational intelligence.<br/>Artificial intelligence.<br/>Mathematical optimization.<br/>Computational Intelligence.<br/>Artificial Intelligence.<br/>Optimization.
<br/><br/><label>LC Class. No.: </label>Q342 
<br/><br/><label>Dewey Class. No.: </label>006.3